A great number of new applications and websites leverage the breadth of the World Wide Web to deliver requested or desirable information to users, and many of them do so with the help of popular search engines. Despite the availability of a vast wealth of user information, conventional search engines fail to meaningfully incorporate this information into the display of search results. For example, search engine users regularly repeat the same searches over time, or they perform similar searches comprising overlapping search results. Existing search engines, however, do not incorporate information about the users' prior interactions with their search results. They do not remember which results users liked, disliked, found useful, etc. As a result, users may be forced to unnecessarily repeat their research efforts.
User information, in this context, may include individual user interactions, interests and preferences, as well as the collective interactions, interests, and preferences of many users. User information may also include, for example, identifications of particular web pages, documents, or other information resources that users believe are useful or interesting. Similarly, user information may include identifications of information resources that users believe are not useful or interesting. Further, user information may include semantic information about information resources that associates certain resources with other related information resources. For example, co-pending U.S. patent application Ser. No. 14/664,166, entitled “Deriving Semantic Relationships Based on Empirical Organization of Content by Users,” describes embodiments for deriving semantic relationships among information resources based on user actions.
It would be beneficial if users could interface with popular search engines in a manner that more precisely leverages user information to identify, filter, modify, and present search results in a more productive manner.